faire · San Francisco, CA
Skills: Accessibility
About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this role Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of Applied AI/ML Scientists specialize in developing algorithmic solutions for recommender systems, spend optimization, lifetime value (LTV) predictions, and much more. Our ultimate goal is to empower local retail businesses with the tools they need to succeed. At Faire, the Data team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. As the tech lead for Acquisition, you will own data science vision, strategy, and execution for how Faire finds and acquires the independent retailers who shop on our marketplace. You will build the models that decide where and how much we spend across paid channels, predict the long-term value of prospective retailers, generate the landing pages and content that bring them to Faire, and shape the experience retailers have before they sign up. You will lead a small t…
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